Does it make sense to use the slope of trend line from a regression as a ratio between x and y The regression plots Hours (y) vs jobs (x). Let's say the equation is: y = 0.4x + 90
Is it okay to say that the time for each job is 0.4 hours?
 A: I presume $x$ is number of jobs and $y$ is number of hours to complete it. It's not correct to say that time for each job is 0.4 hours because you have a (pretty large) bias term. This means you have a fix cost. Performing one job takes $90.4$ hours, two jobs $90.8$ hours etc. So, you can say that each additional job takes 0.4 hours. And, time for each job asymptotically approaches $0.4$ hours, i.e. as $x\rightarrow \infty$.
A: Not exactly. Assuming a simple linear model $y = \beta_0 + \beta_1 x + \epsilon$, the parameter $\beta_1$ (in this case $0.4$) represents the effect of a one-unit change in the corresponding $x$ (here jobs) covariate on the mean value of the dependent variable, $y$ (here hours), assuming that any other covariates remain constant at some value. 
As the $\beta_0$ (the intercept) is $90$, probably there are some other factors that require on average $90$ hours to be taken into account. 
It is more relevant to say that each additional job requires an additional $0.4$ hours.
